Neuroendocrinology of the lung revealed by single-cell RNA sequencing

Pulmonary neuroendocrine cells (PNECs) are sensory epithelial cells that transmit airway status to the brain via sensory neurons and locally via calcitonin gene-related peptide (CGRP) and γ- aminobutyric acid (GABA). Several other neuropeptides and neurotransmitters have been detected in various species, but the number, targets, functions, and conservation of PNEC signals are largely unknown. We used scRNAseq to profile hundreds of the rare mouse and human PNECs. This revealed over 40 PNEC neuropeptide and peptide hormone genes, most cells expressing unique combinations of 5–18 genes. Peptides are packaged in separate vesicles, their release presumably regulated by the distinct, multimodal combinations of sensors we show are expressed by each PNEC. Expression of the peptide receptors predicts an array of local cell targets, and we show the new PNEC signal angiotensin directly activates one subtype of innervating sensory neuron. Many signals lack lung targets so may have endocrine activity like those of PNEC-derived carcinoid tumors. PNECs are an extraordinarily rich and diverse signaling hub rivaling the enteroendocrine system.


Introduction
Pulmonary neuroendocrine cells (PNECs) are neuroepithelial cells scattered throughout the epithelium lining the airways, many as solitary cells and others in clusters of ~30 cells (called neuroepithelial bodies or NEBs) at airway branchpoints (Scheuermann, 1997). PNECs are thought to monitor airway

Results
Enrichment and single-cell RNA sequencing of mouse pulmonary neuroendocrine cells Because PNECs are among the rarest of lung cell types, they are not found, or only poorly represented, in lung scRNA-seq studies (Han et al., 2018;Tabula Muris Consortium et al., 2018;Travaglini et al., 2020, https://www.lungmap.net/). We therefore genetically labeled PNECs using a Cre recombinasedependent fluorescent reporter (ZsGreen) by tamoxifen induction of Ascl1 CreER/+ ; Rosa26 LSL-ZsGreen/+ mice, and then depleted other, abundant lung cell populations and enriched for the labeled PNECs prior to scRNA-seq ( Figure 1A, Figure 1-figure supplement 1A and B). Poly-adenylated mRNA from each sorted ZsGreen + or control cell was reverse transcribed and PCR-amplified using Smart-seq2 protocol , and the obtained cDNA was used to generate libraries sequenced to a depth of 10 5 -10 6 reads/cell and quantified to determine expression levels of each gene in each cell. Cells with similar expression profiles were computationally clustered (Butler et al., 2018), and the cell type identity of each cluster was assigned based on expression of canonical lung cell type markers including Ascl1, Calca, and Chga for PNECs ( Figure 1-figure supplement 1C). After filtering low quality cells and cell doublets, we obtained high quality transcriptomes (2025±450 genes (mean ± SD) detected per cell) of 176 PNECs. We also obtained 358 other pulmonary cells (Figure 1-figure  supplement 1D) including Ascl1 lineage-labeled glial cells.
Some of the peptidergic genes including Calca, Igf2, and granins (Chga,Chgb,Scg2,Scg3,Scg5,Pcsk1n) were expressed in most PNECs analyzed, but others were detected in minor subpopulations ( Figure 1E, Supplementary file 4). We analyzed peptidergic gene expression in our second scRNA-seq dataset of 92 PNECs that used a different strategy for PNEC labeling and capture (Ouadah et al., 2019) and obtained a similar distribution of peptidergic gene expression, with the exception of Pcsk1n (expressed in 14% of PNECs vs. 62% in original dataset) and Ucn2 (34% vs 0%) ( Figure 1E, Supplementary file 4). We also validated expression of eight peptidergic genes and determined the distribution and abundance of the expressing cells in vivo by immunostaining and multiplex smFISH. The canonical mouse PNEC marker and neuropeptide CGRP (Calca) was detected in 95% of PNECs by scRNA-seq, 95% of PNECs by immunostaining (n=237 scored cells in 3 mice) ( Figure 1F), and 94% by smFISH (n=100 scored cells in 2 mice) ( Figure 1D). Cartpt was detected in 34% of PNECs by scRNA-seq and twice that by immunostaining (68%) ( Figure 1F) and smFISH (67%) ( Figure 1G). smFISH also confirmed PNEC expression of the six other peptidergic genes examined (Scg5, Chga, Agt, Pomc, Nmb, Adcyap1) but generally gave higher percentages of expressed PNECs especially for the less abundantly expressed genes, implying smFISH is more sensitive than scRNA-seq in detecting gene expression ( Figures 1G and 2B). Indeed, when PNECs with very low expression (1-4 mRNA puncta detected per cell) were not included in the smFISH quantification, there was excellent agreement between smFISH and scRNA-seq values ( Figure 1G). The broadly expressed peptidergic genes Calca, Scg5, Chga, and Cartpt were detected in both solitary and clustered PNECs, and the four genes detected in smaller subpopulations (Agt, Pomc, Nmb, Adcyap1) were most commonly detected in NEBs at bronchial branchpoints, with local clustering observed within a NEB of the Pomc-expressing cells (Figure 2-figure supplement 1A).
We conclude that PNECs express dozens of peptidergic genes, nearly half (47%) of all annotated peptidergic genes and over an order of magnitude more than previously known, with most expressed in rare PNEC subpopulations. Statistical modeling of our PNEC sampling in scRNA-seq indicated we likely achieved saturation of PNEC peptidergic genes ( Figure 2-figure supplement 1B), however the value of 43 expressed genes is a lower limit because even more sensitive methods of detecting gene expression in individual cells such as smFISH could identify additional PNEC peptidergic genes.

PNECs express myriad combinations of peptidergic genes
The scRNA-seq analysis showed that individual mouse PNECs expressed 7.2 ± 1.9 (mean ± S.D.) peptidergic genes, with some cells expressing up to 13 (range 2-13). Remarkably, almost every PNEC expressed a different combination of peptidergic genes: 154 peptidergic patterns were identified among the 176 PNECs analyzed (Figure 2A). Because the number of combinations detected by scRNA-seq could be artificially inflated by 'technical dropout' (failure to detect an expressed gene), we also scored peptidergic combinations by the more sensitive technique of multiplex smFISH ( Figure 2B). For the eight peptidergic genes probed in 100 PNECs, we identified 30 different cellular patterns of expression, similar to the 24 patterns detected by scRNA-seq for the same eight genes ( Figure 2C and D). Thus, each PNEC expresses multiple peptidergic genes and in an extraordinary number of combinations.
The number and diversity of neuropeptides and peptide hormones expressed by PNECs is further expanded by post-transcriptional processing. Some of the expressed genes are alternatively spliced to produce transcripts encoding different neuropeptides or hormones with distinct expression patterns and physiological functions. For example, Calca, which encodes the classical PNEC neuropeptide CGRP, can be alternatively spliced to generate transcripts encoding the thyroid hormone calcitonin that regulates calcium homeostasis (Amara et al., 1980;Amara et al., 1982). Mapping of PNEC scRNA-seq reads at the Calca genomic locus revealed that Calca transcripts are alternatively spliced  0   5  10  20  30  40  50  60  70  80  90  100  1 10  120  1 30  140  1   Many neuropeptide and peptide hormone mRNAs are translated as larger pre-pro-peptides that are proteolytically processed and modified to generate up to eight different neuropeptides and/or peptide hormones, typically with different expression patterns and functions (Supplementary file 5), which would further increase the PNEC signaling repertoire. A classic example is POMC, cleaved by proprotein convertases PCSK1 and PCSK2 to generate ACTH (adrenocorticotrophic hormone), MSH (melanocyte stimulating hormone), β-endorphin as well as others by additional processing events ( Figure 3D). We surveyed expression of the processing enzyme genes in our scRNA-seq dataset ( Figure 3E) and found that nearly all PNECs expressed Pcsk1 ( Figures 1C and 3F) and a subset of those expressed Pcsk2, predicting that POMC is processed in PNECs into multiple neuropeptides and peptide hormones including ACTH, α3-MSH, and β-endorphin. Confocal imaging of PNEC immunostains for POMC, CGRP, and calcitonin showed that each co-expressed neuropeptide or peptide hormone localized largely to its own secretory vesicles ( Figure 3G), even ones expressed from the same gene (CGRP and calcitonin, Figure 3C), implying distinct vesicular targeting and packaging pathways. Thus, post-transcriptional and post-translational processing expands the number and diversity of peptidergic signals expressed by each PNEC, and their separate vesicular packaging raises the possibility of differentially regulated release and impact on targets.

Diverse targets of PNEC signals
To predict the direct targets of the PNEC signals, we searched our molecular cell atlas of the lung, comprising the full expression profiles of nearly all lung cell types (Travaglini et al., 2020) and pulmonary sensory neurons (Liu et al., 2021), for cells that express the cognate receptors (Supplementary file 5). The only previously defined targets of PNEC signals are a subpopulation of immune cells (IL5 lineage-positive) proposed to be attracted to PNECs by secreted CGRP in a mouse model of asthma (Sui et al., 2018), and goblet cells, which are increased in macaque and mouse models of inflammation through neurotransmitter GABA from PNECs (Barrios et al., 2019;Sui et al., 2018). Recently, CGRP from tracheal TNECs has been found to support tracheal epithelial cells following hypoxic injury .
Receptors for serotonin and GABA, the two major PNEC neurotransmitters, are expressed by the two pulmonary sensory neuron (PSN) subtypes that innervate NEBs (PSN4 (Olfr78+) and PSN7 (Calb1+); Figure 4A), identifying the first signals from PNECs to these afferent fibers that communicate pulmonary sensory information to the brain. GABA receptor genes were also expressed in goblet cells, supporting the conclusion from macaque and mouse models and identifying the specific GABA receptor subunit as GABRP, as well as in club cells, epithelial cells that neighbor PNECs ( Figure 4figure supplement 1). Receptors for the neurotransmitters glutamate, dopamine and histamine predicted by our transcriptomic data to be produced by rare PNECs (see above) were also expressed in innervating PSNs ( Figure 4A) as well as in plasmacytoid dendritic cells (glutamate receptor Grm8) and basophils (histamine receptor Hrh4; Figure 4-figure supplement 1B).
Of the more than 90 neuropeptides and peptide hormones encoded by the 43 PNEC peptidergic genes, 36 have known receptors (Supplementary file 5). The lung expression patterns of these receptors are shown in Figure 4B, identifying dozens of lung cell types that can directly receive PNEC peptidergic signals. Indeed, every lung cell type expressed a receptor for at least one PNEC peptidergic signal, and most expressed receptors for multiple signals. This suggests that PNECs can function as a signaling hub broadcasting airway sensory information to cells throughout the lung. The richest targets by far were the innervating pulmonary sensory neurons PSN4 and PSN7, which expressed NEBs from two wild-type mice). Filled circles, expressed peptidergic gene. (D) Percent of PNECs expressing each of the 24 observed combinations of the same eight peptidergic genes in scRNA-seq dataset (n=176 PNECs).
The online version of this article includes the following figure supplement(s) for figure 3:   Npw   We experimentally validated one of the inferred signaling interactions-the predicted angiotensin signal from PNECs to pulmonary sensory neurons. Angiotensin is among the most medically important hormones because of its key role in vasoconstriction and blood pressure regulation ( Figure 4-figure supplement 2A), and because one of its processing enzymes (angiotensin converting enzyme 2, ACE2) also serves as the entry receptor for SARS and Covid-19 coronaviruses. Indeed, the lung plays an essential role in this hormone pathway by providing angiotensin converting enzyme (ACE), the target of a ubiquitous class of anti-hypertensive drugs (ACE inhibitors), that proteolytically processes circulating angiotensin I peptide (Agt I) into the potent vasoconstrictor Agt II. Our discovery that PNECs express angiotensinogen (Agt), the preprohormone for Agt II, reveals a pulmonary source of the hormone, and our molecular cell atlas points to three potential lung targets: pericytes, and the PSN4 and PSN7 pulmonary sensory neurons that innervate NEBs, each of which selectively expressed Agt II receptor gene Agtr1a ( Figure 4B).

PNECs are diverse, multimodal sensors
Classical physiological studies of PNECs indicate that signal secretion is triggered by a variety of stimuli including hypoxia, hypercapnia, mechanical stimuli, and allergens (Lembrechts et al., 2012;Livermore et al., 2015;Sui et al., 2018;Youngson et al., 1993). However, the full diversity of PNEC sensory functions are unknown, and the molecules that mediate these functions have only recently begun to be identified (Nonomura et al., 2017). To more fully elucidate PNEC sensory functions and the molecules that mediate them, and to determine how sensors are paired with the myriad PNEC signals described above, we curated a list of over 1500 mouse genes encoding extant mammalian sensory receptors and their homologues (Supplementary file 6) including ones previously implicated in PNEC sensory function, then searched our scRNA-seq dataset for ones selectively expressed in PNECs.
PNECs are proposed to function in CO 2 sensing because they can be activated by hypercapnic challenge (Lauweryns et al., 1977), and by bicarbonate and acid in vitro (Ebina et al., 1997;Livermore et al., 2015), a response dependent on carbonic anhydrase, but the proteins that mediate this function are unknown. PNECs selectively expressed the classic acid-sensing potassium channel TREK (Kcnk3), and rare PNECs expressed acid-sensing sodium channels ASIC3 (Accn3) and ASIC4 (Accn4) ( Figure 5A, Figure 5-figure supplement 1A). Expression of the widely-distributed cytoplasmic carbonic anhydrase Car2 gene was not detected in PNECs, but some expressed membrane-bound Car12 and the carbonic anhydrase-related gene Car11 ( Figure 5A, Figure 5-figure supplement  1A).
One of the first and still the most prominent proposed function of PNECs is as airway oxygen sensors because they can be activated by hypoxic challenge in vivo (Lauweryns et al., 1978) and in cultured lung slices or as isolated PNECs (Youngson et al., 1993). The oxygen sensing mechanism is still uncertain but the dominant hypothesis proposes that low oxygen reduces H 2 O 2 generation by a membrane-bound NADPH oxidase (heterodimer of gp91phox/Cybb and p22phox/Cyba, plus regulatory subunits p47phox/Ncf1, p67phox/Ncf2), which inhibits an oxygen-sensitive potassium channel (Kv3.3/Kcnc3 and Kv4.3/Kcnd3) that activates L-type voltage-gated calcium channels (Fu  ; acid-sensing (Acid); CO 2 -sensing, carbonic anhydrases (CO 2 ), chemosensing (Chemo). Note the 56 different combinations of expressed sensory genes, with most PNECs predicted to be multimodal because they express more than one class of sensor. (B) Schematics of sensor and signal genes expressed by three individual PNECs. Number in center indicates sensory gene combination in panel A. Genes above number are expressed sensory genes, and genes below number are expressed signal genes with arrows indicating lung targets (cells that express receptor) or signals without identified lung targets that may enter circulation (circ) to target other organs.?, signals without known receptors. Imm, multiple immune populations; PSN, pulmonary sensory neurons.
The online version of this article includes the following figure supplement(s) for figure 5:    Youngson et al., 1993), triggering neurosecretion that may act locally or be propagated to the brainstem breathing center. We did not detect PNEC expression of NADPH oxidase subunits p91phox/Cybb, p47-phox/Ncf1, or p67-phox/Ncf2, and p22phox/Cyba was broadly expressed in all cells ( Figure 5-figure supplement 1A). Kv3.3/Kcnc3 and Kv4.3/Kcnd3 were detected only at low levels or in rare cells (previous reports of Kv3.3/Kcnc3 and Kv4.3/Kcnd3 expression by PNECs were based on in situ hybridization studies of fetal rabbit and neonatal human lung (Gonzalez et al., 2009;Wang et al., 1996), so there may be developmental or species-specific differences in its PNEC expression). Although we did not detect substantial expression of these previously implicated channels, we found robust and selective PNEC expression of many other potassium channel genes ( Figure 5-figure supplement 1B; e.g. voltage-gated: Kcnc1, Kcnc2,Kcnb1,Kcnv1,Kcnf1,Kcnq2,Kcnq5,Kcnh2,Kcnh6,Kcnh7,Kcnh8; cyclic-nucleotide gated Na/K channel : Hcn1, Hcn2, Hcn3, Hcn4; calcium-activated: Kcnn3; 2-pore: Kcnk1, Kcnk3) that could contribute to the hypoxia-sensitive potassium current required for PNEC secretion. We also did not detect selective expression in PNECs of any of the genes (mitochondrial respiratory complexes) implicated in the mitochondrial hypothesis of oxygen sensing (Mulligan et al., 1981;Quintana et al., 2012;Stettner et al., 2011;Figure 5figure supplement 1A). Thus, the identity of the acute oxygen sensor in PNECs remains uncertain, although several of the newly identified PNEC potassium channels are appealing candidates. Chronic hypoxia also influences PNECs, and hypoxia inducible factor Hif1a is expressed though not selectively in PNECs, whereas Hif3a is a PNEC-selective family member ( Figure 5-figure supplement 1A).
Primate PNECs have been proposed as volatile chemical sensors based on expression of olfactory receptors OR2W1 and OR2F1 in some solitary human PNECs, and the response of PNECs in tracheobronchial cultures to nonanal and other chemicals (Gu et al., 2014). We identified 19 olfactory and two pheromone receptor superfamily genes expressed in rare PNECs ( Figure  Individual PNECs express multiple sensors and are predicted to sense multiple modalities. For example, one PNEC (combination 55) expressed mechanoreceptor/transducer genes Piezo2, Casr, and Lhfpl5, acid-sensitive channel Kcnk3, and chemoreceptors Olfr90, Olfr92, and Vmn2r29 ( Figure 5A and B). Individual PNECs expressed different combinations of sensory genes, indicating diversity in their sensory roles ( Figure 5A and B). Comparison of the sensors and signals expressed in each PNEC did not identify any strong correlations, suggesting that specific sensory inputs are coupled to different output signals in different PNECs.

Human PNECs also show diverse sensory, signaling and target profiles
To explore the generality and biomedical significance of the properties of mouse PNECs uncovered by scRNA-seq, we performed a similar analysis of human PNECs. Although human PNECs are also extremely rare, in our scRNA-seq study of ~75,000 human lung cells (Travaglini et al., 2020) we obtained expression profiles of 55 PNECs. We analyzed these PNEC profiles as we did above for mouse PNECs and found that, even with this more limited sample, all the features uncovered for mouse PNECs are also apparent for human PNECs, although in more extreme form for some features and with species-specific specializations.
Like mouse, human PNECs have a large and diverse signaling output. Human PNECs express biosynthetic genes for neurotransmitters serotonin (TPH1) and GABA (GAD1) (Supplementary file 8), the major neurotransmitters of mouse PNECs. Some human PNECs are also likely glutamatergic because 14% expressed glutamate vesicular transporter SLC17A6, and some may be catecholaminergic or glycinergic because rare PNECs expressed key catecholamine synthetic enzymes (DBH, PNMT) or glycine re-uptake transporter SLC6A5 (Supplementary file 8). Expression of dopaminergic genes was detected in rare mouse PNECs but none of the analyzed human PNECs.
The human lung cell expression patterns of receptors for the 32 PNEC peptidergic signals with known receptors are shown in Figure 6-figure supplement 3A, identifying potential direct targets in lung. As for mouse, expression patterns were diverse and almost all lung cell types expressed receptors for one or more signals, implying human PNECs can also transmit pulmonary sensory information throughout the lung. The predicted targets of the conserved PNEC signals were also largely conserved, for example broad stromal and vascular targeting by inhibin, immune cell targeting by CGRP and VGF, and pericyte targeting by angiotensin. Autocrine signaling appears prominent, as PNECs express receptors for ghrelin and erythropoietin, one of the human-specific signals, and almost every PNEC neurotransmitter (GABA, glutamate, dopamine, and epinephrine/norepinephrine; Figure 6-figure supplement 3B). Curiously, the sole PNEC autocrine signal identified in mouse, IGF2, was not detected in any profiled human PNEC ( Figure 6A, Supplementary file 4). No receptor expression was detected in lung for nearly half (45%, 15 of 33) the human PNEC peptidergic signals, including 10 of the 14 human-specific signals. While some of these signals may target pulmonary sensory neurons or rare pulmonary cells not captured in our human lung atlas, others may enter circulation and target sites beyond the lung.
scRNA-seq profile of a human lung carcinoid: amplification of a rare PNEC PNECs are the presumed origin of a variety of human lung neuroendocrine tumors (Travis et al., 2015) that can cause diverse ectopic hormone syndromes such as classic carcinoid syndrome (wheezing, flushing, diarrhea, increased heart rate), Cushing's syndrome (Arioglu et al., 1998), and acromegaly (Athanassiadi et al., 2004). To determine the full sensory and signaling potential of a PNEC tumor and their relationship to those of normal PNECs, we obtained scRNA-seq profiles of NE tumor cells of a lung carcinoid from a 51-year-old female patient with onset of idiopathic hypertension in the year preceding therapeutic lung resection. The profiled tumor cells expressed most general PNEC markers (e.g. SCG5, CHGB, SCG2, PCSK1N, CHGA, SCG3) indicating retention of PNEC identity. However, they did not recapitulate the full spectrum of PNEC diversity in their sensory and signaling gene profiles ( Figure 6D and E). Some peptidergic genes such as CALCA and GRP that are expressed in almost all normal PNECs were expressed in few if any tumor cells, whereas NPW, NMB, and CARTPT that are expressed in only rare PNECs were expressed in most (NPW) or many (NMB, CARTPT) of the tumor cells ( Figure 6D). Likewise, the tumor cells lacked expression of the common PNEC mechanosensor PIEZO2 but showed broad expression of the acid-sensitive channel KCNK3 and opsin OPN1SW, which is expressed only by rare normal PNECs (Figure 6-figure supplement 4). This suggests that proliferating tumor cells retain a "memory" (albeit imperfect) of the expression profile of the PNEC from which they originated. And, because this tumor's unusual expression profile nearly matched that of a rare normal PNEC (#50, Figure 6B and C), which like the tumor cells expressed NPW, NMB, CARTPT, KCNK3, and OPN1SW and lacked expression of common PNEC genes CALCA, GRP, and PIEZO2 ( Figure 6D and E, Figure 6-figure supplement 4), we suggest that this carcinoid arose by transformation of a cell similar to PNEC #50. Tumor cell expression of NPW may have caused the patient's hypertension because the active peptide (NPW-23) is a circulating hormone that regulates vascular tone and has been proposed to play a role in the pathophysiology of hypertension (Ji et al., 2015;Yu et al., 2007).       To determine the peptidergic signaling profiles of other lung carcinoids, we analyzed peptidergic gene expression in 111 human lung carcinoids profiled by bulk RNA-seq (Alcala et al., 2019). This revealed prominent expression of 70% (28 of 40) of the normal human PNEC peptidergic genes, including new genes we identified in rare subpopulations of normal PNECs, in at least some of the tumors (Figure 6-figure supplement 6). Ten peptidergic genes expressed by lung carcinoids, including four previously detected in clinical samples (GHRH, PENK, TAC1, VIP), were not found in our normal PNECs; however, all of these were expressed in only rare carcinoids so may be expressed in rare PNECs and if so should be identified on further PNEC profiling. Interestingly, some of the peptidergic genes expressed in only minor subpopulations of normal PNECs (e.g. NPW, NPPA, SST, CARTPT) were detected in many carcinoids, whereas the nearly ubiquitous PNEC peptidergic gene CALCA was absent from most carcinoids. This suggests that not all normal PNECs are equally susceptible to carcinoid transformation.

Discussion
By single-cell expression profiling of hundreds of the exceedingly rare PNECs in mouse and human, we discovered they express over 40 peptidergic genes, nearly half of all such genes including many classic hormones. Individual PNECs express up to 18 peptidergic genes, with almost every cell expressing a distinct combination. The diversity of expressed signals is further increased by alternative splicing, and by post-translational processing as inferred from expression of prohormone processing genes. These diverse signals can directly target a wide array of cell types in the lung, predicted by expression of the cognate receptors, including almost every cell type across all five tissue compartments: epithelial (including putative autocrine PNEC signals), endothelial, stromal, immune, and neural. The richest targets are pulmonary sensory neurons (PSNs) that innervate PNECs. We confirmed one predicted signal to PSNs, angiotensin (Agt II, mature product of Agt), can directly activate a recently identified PSN subtype (PSN4) that innervates PNECs, expresses its receptor (Agtr1a), and projects to the brainstem to regulate respiratory rate Liu et al., 2021;Diaz de Arce, et al., unpublished data. Hence in addition to its classical role as a circulating vasopressor whose receptor is targeted by major antihypertensive drugs, Agt II may serve as a neuromodulator in the breathing circuit. Eighteen other PNEC signals are also classical hormones, but unlike Agt II their receptors are not expressed in any cell types in the lung cell atlases, suggesting that PNECs could contribute to the circulating pool of these hormones. PNECs are thus extraordinarily rich and diverse signaling hubs that produce scores of neuropeptides and peptide hormones that can signal directly to many cells in the lung, to the brain through pulmonary sensory neurons, and potentially to cells throughout the body through the circulation.
PNECs are scattered throughout the airway epithelium and form large clusters at bronchial branchpoints, so they are ideally positioned to serve as sentinels that monitor inhaled air and airway status. Our single-cell data imply that each PNEC is in fact a multimodal sensor, expressing a distinct combination of mechanical, thermal, and acid sensors along with carbonic anhydrases important in CO 2 sensing, diverse chemosensors including olfactory receptors, vomeronasal receptors and taste receptors, and even light-sensing opsins. Different combinations of sensors are co-expressed in individual PNECs along with different combinations of signals ( Figures 5B and 6C). Because the peptidergic signals are packaged in separate vesicles, secretion of each signal could be independently regulated, presumably in response to activation of a different sensor (or sensor combination). In this way PNECs can simultaneously monitor many aspects of airway status at many positions along the airway, and selectively transmit this information to target cells in the lung, the brain, and the rest of the body.
In many ways PNECs resemble enteroendocrine cells (EECs), the sentinels scattered along the gut epithelium to monitor nutrients, microbial products, and other luminal contents and signal that information locally in the gut to coordinate ingestion, absorption, metabolism, and disposal, and throughout the body and brain to regulate mood and appetite (Bai et al., 2019;Bellono et al., 2017;Kaelberer et al., 2018). The enteroendocrine system is commonly called the 'gut-brain axis' and is considered the largest endocrine organ because of its many endocrine cells and signals. Our data suggest it may be rivaled or even surpassed by the pulmonary neuroendocrine system, which expresses more than double the ~20 signals produced by EECs (Beumer et al., 2020). Each EEC apparently expresses only one or a few peptidergic signals and neurotransmitters, which define 12 classical EEC subtypes (Worthington et al., 2018), whereas individual PNECs express 5-10 times more and their expression patterns define at least an order of magnitude more molecular subtypes. While PNECs have long been speculated to serve as local signaling centers in the lung and fast conduits of sensory information to the brain through afferent sensory neurons, our data suggest that like EECs they also serve a more global endocrine function. This would explain why the basal surface of some PNECs, where secretory vesicles are densely packed, are apposed to fenestrated capillaries (Lauweryns et al., 1973). Although PNEC contribution to circulating hormone pools under normal physiological conditions is yet to be demonstrated, they contribute at least under pathological conditions. Indeed, we found that the extensive PNEC signaling repertoire described here including most of newly identified peptidergic genes, were collectively expressed in the 111 available cases of profiled human lung carcinoids. An individual human carcinoid, however, expresses a discrete set of signals resembling that of a normal PNEC, suggesting that each such tumor amplifies the set of signals expressed by the tumor-initiating PNEC, thereby explaining the diversity of carcinoid syndromes (Limper et al., 1992;Pernow and Waldenström, 1957;Shalet et al., 1979). PNECs may comprise a second global signaling axis we dub 'the lung-brain axis'.
This new understanding of PNEC function and their extraordinary diversity, including many sensor and signaling genes detected in only a single profiled cell, required pre-enrichment (mouse) or massive profiling (human) to obtain just the first few hundred expression profiles of these exceedingly rare cells. The neuroendocrinology of the lung our study reveals has broad implications for medicine even beyond NE cell tumors (Rudin et al., 2019;Travis et al., 2015;Young et al., 2011), including the many other pulmonary diseases such as asthma (Sui et al., 2018), SIDS (Cutz et al., 2007;Mou et al., 2021), and bronchopulmonary dysplasia (Gillan and Cutz, 1993) that have been associated with PNEC abnormalities and perhaps now extending to diseases outside the lung. The results already have implications for the Covid-19 pandemic because SARS-CoV-2 virions use an angiotensin pathway regulator (ACE2) to enter and destroy lung cells and cripple gas exchange along with the ability of the patient to sense the deficit. Although expression of angiotensinogen and many other PNEC sensory and signaling genes are conserved so their functions can be explored in mice, we also uncovered 13 human-specific PNEC signaling genes encoding classical hormones (e.g. ACTH (POMC), GRP, TRH, AMH, CCK). Hence the lung-brain axis may be especially prominent in humans.

Data and code availability
Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead author Christin Kuo (ckuo@stanford.edu) or lead contact Mark Krasnow (kransow@stanford.edu). All raw and processed data with accompanying metadata from scRNA-seq of mouse and human PNECs will be submitted to the Gene Expression Omnibus (GEO) database https://www.ncbi.
nlm.nih.gov/geo. Raw data consists of fastq files corresponding to paired-end reads for each cell, and processed data is in the form of a raw gene counts matrix. All code used to generate data objects and plots is available at github: https://github.com/sdarmanis/Neuroendocrine_scRNA-seq copy archived at swh:1:rev:c411aa9cce13aba895d521ed979f8a7b47e2d1bd (Kuo, 2022) and http://github.com/ cskuo/NE_scRNA-seq.

Experimental model and subject details Animals
all possible combinations in approximately equal proportions (variance up to 10%). Plates with sorted cells were sealed with microplate sealing film, vortexed 3-5 s, centrifuged at 1000xg for 1 min, and immediately placed on dry ice and stored at -80 °C until complementary DNA (cDNA) generation and sequencing.
Single-cell mRNA sequencing RNA from individual sorted cells was reverse transcribed to cDNA amplified, and Illumina sequencing libraries prepared as previously described (Darmanis et al., 2017). Briefly, 96-well plates containing single-cell lysates were thawed on ice, heated to 72 °C for 3 min and immediately put back on ice. For cDNA synthesis, 6 µl of reverse transcriptase mix (1 X First-Strand Buffer (Takara Bio, 639538) with 100 U SMARTScribe Reverse Transcriptase (Takara Bio, 639538), 10 U Recombinant RNase Inhibitor (Takara, 2313 A), 8.5 mM DTT (Invitrogen, P2325), 0.4 mM Betaine (Sigma, B0300-5VL), 10 mM MgCl 2 (Invitrogen, AM9530G) and 1.6 µM template switching oligonucleotide containing one locked nucleic acid-modified guanosine (+G) at 3'end (5′-AAGC AGTG GTAT CAAC GCAG AGTA CATr GrG+G) (Exiqon)) were added to each well, and the reactions were incubated at 42 °C for 90 min followed by 70 °C for 5 min. For PCR amplification of cDNA, 15 µl of PCR mix (1 x KAPA HiFi HotStart ReadyMix (Kapa Biosystems, KK2602) with 0.16 µM 1SPCR (one step PCR) oligonucleotide (5′-AAGC AGTG GTAT CAAC GCAG AGT) (IDT) and 0.56 U of Lambda Exonuclease (New England Biolabs, M0262L)) was added to each well, followed by thermal-cycling at: (i) 37 °C for 30 min, (ii) 95 °C for 3 min, (iii) 21 cycles of 98 °C for 20 s, 67 °C for 15 s and 72 °C for 4 min, and (iv) 72 °C for 5 min. Amplified cDNA was purified using 0.7 x AMPure XP beads (Beckman Coulter, A63880) then analyzed by capillary electrophoresis on a Fragment Analyzer (Advanced Analytical Technologies) and the concentration of cDNA (in fragment size range 500-5000 bp) adjusted and Nextera DNA sequencing libraries prepared as described (Darmanis et al., 2015). Libraries from wells on each plate were pooled using a Mosquito liquid handler (SPT Labtech), purified twice using 0.7 x AMPure XP beads, and library pool quality assessed on a Fragment Analyzer. Libraries from 679 single cells were sequenced (75 bp paired-end reads) on a NextSeq 500 (Illumina) using High-output v2 kits (Illumina). Raw sequence reads were demultiplexed using bcl2fastq (v1.8.4,Illumina), and remaining sequences aligned to the mouse reference genome (GRCm38-mm10, UCSC, supplemented with Zsgreen1 sequence) with STAR (v2.5.2b, default parameters except Stranded set to false and Mode set to intersection-nonempty), and the number of reads that mapped to each annotated gene (gene counts) determined with HTSEQ (v0.6.1p1, default parameters except Stranded set to false and Mode set to intersection-nonempty) (Anders et al., 2015). Cells with less than 50,000 mapped reads or less than 1000 detected genes were excluded as a quality metric, leaving 534 cell expression profiles for further analysis.

Analysis of CALCA alternative RNA splicing in PNECs
Sequence reads from both mouse and human PNEC scRNA-seq datasets were aligned to mouse mm10 and human gh38 reference genomes, respectively, using STAR, and the BAM (binary compressed version of sequence alignment map) output visualized by sashimi plots of the Calca (mouse) and CALCA (human) genomic loci using Integrative Genomics Viewer (IGV v2.4.14) (Katz et al., 2010;Robinson et al., 2011) and the mouse CGRP (RefSeq ID: NM_001289444) and calcitonin (NM_001305616), and human CGRP (NM_001033953) and calcitonin (NM_001741) reference mRNA sequences.

Validation set of mouse PNEC scRNA-seq profiles
A second set of adult mouse PNECs that were lineage-labeled, purified, and profiled by scRNA-seq as described Ouadah et al., 2019 was used as validation set. Briefly, PNECs were lineagelabeled by tamoxifen administration to adult (age 2-3 months) Ascl1 CreERT2 ;Rosa26 LSL-ZsGreen or CGRP CreERT2 ;Rosa26 LSL-ZsGreen mice, and whole lungs (excluding trachea) were processed into a single cell suspension. Red blood cells were lysed, and endothelial and immune cells depleted using MACS. Lineage-labeled epithelial cells (ZsGreen + EpCam + ) were sorted by FACS into a single collection tube, and individual cells captured and cDNA generated using an integrated microfluidic platform (Fluidigm C1). cDNA sequencing libraries were prepared in 96 well format and sequenced on a NextSeq 500 (Illumina) device, and obtained sequences were demultiplexed, processed, aligned to individual genes, and quantified to define gene expression levels in each cell. PCA analysis was performed on cell expression patterns using highly variably expressed genes, and identities of cell clusters with related expression patterns assigned based on enriched expression of canonical lung cell type markers. Of the 100 PNEC expression profiles obtained, the eight with 'transitional' profiles were excluded from our analysis. A threshold of 5 transcripts/million (TPM) was used for determining if a gene was expressed.

Human PNECs and carcinoid scRNA-seq analysis
The expression profiles of human PNECs characterized here are from our scRNA-seq analysis of cells from histologically normal lung tissue obtained from therapeutic lobectomies and matched blood from three patients with focal lung tumors; these profiles were used to construct our comprehensive molecular cell atlas of the human lung (Travaglini et al., 2020). Among the profiled cells, a cluster of 66 PNECs was identified by their selective expression of classical markers CALCA and ASCL1. For our PNEC analysis, we excluded all 11 human PNEC profiles obtained by droplet-based 10 X scRNA-seq, which had less extensive expression profiles than the ones profiled by SS2, the plate-based method used here to profile mouse PNECSs. We also excluded one SS2-profiled cell that was designated a PNEC (cell ID: C7_B002464.gencode.vH29) but was an outlier in the original PNEC cluster Travaglini et al., 2020; we found it expressed only one PNEC neuropeptide (DBI) but not any classic PNEC markers (CALCA, CHGA, ASCL1, GRP) or our newly identified PNEC markers (SCGN, PCKS1N, SCG3, SCG5), so it is likely a related but distinct and extremely rare lung cell type. We included in our analysis one SS2-profiled cell that was not originally designated a PNEC (Cell ID: H4.B002460.gencode.vH29), which we found expressed both classic and new PNEC markers (ASCL1, GRP, CHGB, SCGN, SCG2, SCG3, SCG5). In total, our analysis included 55 PNECS, 50 from patient 1 and 5 from patient 3. The SS2 scRNA-seq sequencing reads from these 55 PNECs were re-aligned to the primary assembly of human reference genome GRCH38 (and further analyzed as above), to exclude an alternative contig at the CHGA locus (contig KI270847.1) in the reference genome used in the original analysis (GRCH38.p12) that caused vast undercount of CHGA expression.
The scRNA-seq expression profiles of human carcinoid cells characterized here are from a parallel analysis of one of the tumors in the above study, a typical carcinoid (1.3x0.9 cm) in the left bronchus of the resected left lower lung lobe of patient 3, a 51 year-old female mild adult-onset asthma and recent worsening hypertension. The tumor sample was processed and profiled in parallel with the accompanying normal tissue from this patient, and the 330 cells described here are sorted cells from the epithelial compartment of the tumor sample that were analyzed by SS2 and identified as carcinoid cells by their abundance in the tumor sample and expression of many classic PNEC markers and peptidergic genes, consistent with the underlying clinical and pathological diagnosis. A full description of the carcinoid tumor expression data will be provided elsewhere.

Peptidergic and sensory genes
The comprehensive list of mouse and human neuropeptide and peptide hormones and their genes ('peptidergic genes'; Supplementary file 4) and receptors were compiled from the literature (Kim et al., 2011b;Secher et al., 2016) and an online database (https://www.neuropeptides.nl/), then verified and updated with newly identified receptors by PubMed literature searches (through July 2020) for each included neuropeptide and peptide hormone.
For multiplex single molecule FISH (smFISH), wild-type mouse lungs were perfused, inflated, fixed, imbedded in O.C.T. Compound, and stored as above. Cryosections (12 μm Probed sections were imaged by confocal fluorescence microscopy (Zeiss LSM 880, Airyscan mode), and images were aligned using RNAscope HiPlex Registration software and processed with Zen software (Zeiss). To resolve secretory vesicles immunostained for peptides ( Figure 3C and G), confocal images were acquired in super-resolution mode.
In vitro imaging of mouse pulmonary sensory neuron response to angiotensin Pulmonary sensory neurons (PSNs) were prepared from adult (PN120) Agtr1a Cre/+ ;Rosa26 LSL-tdTom/+ mice that selectively label the two types of PSNs that innervate NEBs (Liu et al, unpublished data). Three to five days prior to PSN isolation, 50 µl (1 mg/mL) of a fluorescent wheat germ agglutinin (WGA-647, Thermo Fisher, W32466) was instilled into the trachea to retrograde label PSNs. After 3-5 days to allow for WGA uptake by PSNs and retrograde transport to their cell bodies in the tenth (vagus) cranial nerve ganglia, mice were euthanized as above and the vagal ganglia were dissected and immediately placed in cold-buffered Hanks Balanced Salt Solution without calcium or magnesium (HBSS, ThermoFisher, 14190144). Ganglia were digested with 60 U papain (Worthington Biochemical, LS003126) in 1 ml HBSS (with 10 mM HEPES pH 7.4, 0.5 mM EDTA, and 0.4 mg/mL L-cysteine) for 10 min at 37 °C. The papain solution was then replaced with 3 ml of a second enzymatic digestion solution (1.5 mg/ml collagenase IV (Worthington, LS004186) and 1 mg/ml dispase (Worthington, LS02109) in HBSS with 10 mM HEPES) and the incubation continued at 37 °C for 30 min, with tube inversion 5 times every 10 min. The sample was centrifuged for 4 min at 400 g, and the pelleted cells were resuspended in 1 ml L-15 medium (Gibco 11415) with 10 mM HEPES (pH 7.4) by three sequential rounds of manual trituration using custom pulled glass micropipettes (Sutter Instrument Company, Model P-87) of successively finer tip diameter (to final range 0.1-0.12 mm). Tips were pre-coated with complete L-15 medium with 10% FBS (Gemini Bio Products, 100-50, diluted in 10 mM HEPES, pH 7.4) to limit neuronal loss. The cell suspension was gently layered on 5 ml of 20% Percoll (Sigma, P4937) in L-15 medium (Gibco, 11415) and centrifuged for 9 min at 400xg to separate dissociated neurons from lower density connective tissue and smaller cells. The cell pellet was resuspended in 2 ml of L15 medium with 10 mM HEPES (pH 7.4), giving a typical yield of ~1000 cells. Cells were transported to the imaging facility at room temperature and centrifuged for 3 min at 750xg. Cells were re-suspended in 100 µl of warm CO 2 -equilbrated DMEM/F12 medium (Gibco, 10565018), and 30-40 µl of the cell suspension were plated in the center of a laminin-coated inset of a poly-lysine-coated 12 mm circular Nunc glass bottom culture dish (Thermo Fisher, 150680), prepared as described below. Cells were incubated at 37 °C for 60-90 min to initiate cell adherence to the inset; although only some neurons adhere during this period, incubations beyond 2 hr caused evaporation of the small volume of medium and decreased neuron viability. DMEM/F12 medium (500 µl) was added to each well, and the cultures were incubated at 37 °C (with 5% CO 2 ) for 12-16 hr to increase cell adherence and equilibrate cells to the culture environment prior to functional imaging. In healthy preparations, typically ~100-150 neurons adhered to the inset and ~10% formed extended projections. (We found that coating of the culture insets with fresh reagents as follows was critical for cell adherence and viability: Poly-lysine coating of clean Nunc glass bottom dishes was done by incubating the dish in a solution of 50 µg/ml poly-D-lysine [Millipore, A-003-E] in HBSS at 37 °C overnight, then washing the dish with HBSS three times and removing residual solution by aspiration; laminin coating of the insets was done by covering insets with a solution of 20 µg/ml laminin [Sigma L2020] in HBSS at 4 °C for at least 45 min [typically 3-4 hr], then carefully removing the laminin solution by aspiration, washing the inset three times with HBSS at 4 °C, and leaving the inset covered in HBSS until cell plating).
For functional imaging, cells were loaded with fluorescent calcium indicator Fluo-4 by incubating cells with 10uµm Fluo-4 (Invitrogen) in HBSS buffered with 10mM HEPES (pH 7.4) for 15-20min. Nunc glass bottom dishes with insets containing cultured neurons were placed on a perfusion chamber platform (Warner Instruments, RC-37W) on a Zeiss 880 LSM confocal microscope stage housed within an incubation chamber adjusted to 37°C and 5% CO 2 ; platform perfusion was by gravity-dependent flow controlled with a stopcock. Cells were continuously perfused with HBSS buffered with 10mM HEPES (pH 7.4), and fields containing retrograde-labeled pulmonary sensory neurons were identified by WGA-647 fluorescence. Calcium imaging data (Fluo-4 flourescence) were collected every second with 488nm wavelength excitation and 500-550nm emission. After baseline recording for 60s, 500nM Angiotensin II peptide (Sigma-Aldrich, A9525) in HBSS with 10mM HEPES (pH 7.4) was perfused for 60s, followed by a wash and re-equilibration with HBSS buffered with 10mM HEPES (pH 7.4) for 3min, and finally a 15-s infusion of 50mM KCl in HBSS buffered with 10mM HEPES (pH 7.4) to assess cell excitability/viability. Following the infusions, the dish was removed from the perfusion chamber and cells immediately fixed with 4% PFA at 4°C for 30-60min for subsequent immunohistochemistry as above to confirm identity of the monitored neurons. For analysis of the time-lapse recordings, Image J software (v2.0) was used to define cell boundaries and determine the mean fluorescence intensity value for each cell in the imaging field at each time point; the obtained fluorescence values were normalized to the average baseline fluorescence value (prior to Angiotensin II exposure) for the cell.

Quantification and statistical analysis
Computational clustering and identification of mouse PNEC scRNA-seq profiles Counts for each gene were normalized across cells, scaled per million and converted to logarithmic scale. Dimensionality reduction was used to compare and cluster the obtained cell expression profiles using Seurat v2.3.4 (Butler et al., 2018). First, genes with highly variable expression across the sample population were identified ('FindVariableGenes'), selecting genes with >1 standard deviation dispersion in mean expression values. Second, the dimensionality of the expression matrix data for the highly variable genes was reduced using principal component analysis (PCA), and the significant principal components (PCs) that captured the majority of variation in the dataset were selected by their standard deviations (PCElbowPlot function) and by examining the top gene loadings in each component as heatmaps. We selected the first 15 PCs, and the 5 genes with the highest PC scores along each PC were inspected for biological relevance and for canonical markers of known lung cell types. Then, the relatedness of cell expression profiles was visualized in two-dimensional tSNE plots ('RunTSNE for R' with perplexity = 30). Third, genes enriched in each cluster of cells with similar expression profiles were identified using Wilcoxon rank sum test with multiple testing correction ('FindAllMarkers'). Cell doublets were identified and removed using Scrublet (Wolock et al., 2019).
The identities of the PNEC cell cluster and the nine other obtained cell clusters were assigned based on enriched expression of canonical lung cell type markers: PNECs (Calca, Ascl1, Chga), multiciliated cells (Foxj1, Ccdc153, Cdhr3), basal cells (Krt5, Trp63, Krt15), AT1 cells (Ager, Rtkn2), AT2 cells (Sftpc, Sftpb), club cells (Scgb3a2, Scgb1a1), endothelial cells (Pecam, Tie1), stromal cell populations 1 and 2 (Col1a1, Col1a2), and glial cells (Gfap, S100b, Plp1). The expression profiles of the 176 obtained high quality PNECs were used for all analyses. To generate the marker list shown in Supplementary file 1, we merged the 534 cells with the mouse lung cell atlas and performed another marker analysis to identify top differentially expressed genes in NE cells compared to non-NE epithelial cells and this analysis of top markers is shown in Figure 1.

Rarefaction analysis to estimate saturation of PNEC neuropeptide diversity
We modeled each PNEC peptidergic expression profile as an incidence sampling of all total possible peptidergic genes expressed by the PNEC population, and estimated the peptidergic diversity using rarefaction and extrapolation analysis, a technique used in ecology to assess species richness (Chao et al., 2014). In this analogy, each 'species' is a peptidergic gene, and a given PNEC that may express any number of distinct peptidergic genes is analogous to a sampling of the total assemblage of species (peptidergic genes). Using the iNEXT package to estimate species richness (Hsieh et al., 2016), we constructed an integrated curve to smoothly link rarefaction (interpolation) and prediction (extrapolation), and the associated 95% confidence intervals, by bootstrapping (N=200). Only the incidence (presence or absence), and not the abundance, of each peptidergic gene RNA was used to estimate the underlying neuropeptide accumulation curve (Chao et al., 2014;García-Ortega and Martínez, 2015). • Supplementary file 3. Expression of neurotransmitter biosynthetic, vesicular loading and reuptake genes in mouse PNECs.
• Supplementary file 4. Summary of mouse and human peptidergic gene expression in PNECs.

• MDAR checklist
Data availability Sequencing data have been deposited in GEO under accession code GSE191178.
The following dataset was generated: Author (